Introduction to modeling of random phenomena.
Introduction of probability: assiomatic costruction of probabiloty spaces. Concept of independence, conditional probability. Bayes Theorem. Random variables: distribution function, expectation, variance (Bernoulli, Binomiale, Geometrica, Binomiale Negativa, Ipergeometrica, Normale, Uniforme, Cauchy, Esponenziale, Gamma, Chi-Quadro, t di Student,...). Markov and Chebychev inequalities. Random vectors. Characteristic functions. Convergence definitions and theorems. Law of large numbers and Central limit theorem. Stochastic simulation.
K. L. Chung, A Course in probability Theory
J. Jacod, P. Protter, Probability Essentials
Ricevimento: Thursday: 14.00-15.30, office 836, or by arrangement made by email.
EMANUELA SASSO (President)
VERONICA UMANITA' (President)
ERNESTO DE VITO
The class will start according to the academic calendar.
The exam consists of a written test and an oral exam.
